Journal
JOURNAL OF INTELLIGENT MANUFACTURING
Volume 33, Issue 1, Pages 103-119Publisher
SPRINGER
DOI: 10.1007/s10845-020-01646-2
Keywords
Industrial dataspace; Machining knowledge; Machining operations control; Knowledge representation; Knowledge graph
Funding
- Natural Science Foundation of China [51975464, 71571142]
- China Scholarships Council (CSC)
- Brunel University London
Ask authors/readers for more resources
The machining processes in advanced workshops are becoming increasingly complex, requiring effective management and utilization of process data and knowledge. This paper presents an industrial dataspace framework for machining workshops, which can manage and process data and knowledge effectively.
The machining processes on the advanced machining workshop floor are becoming more sophisticated with the interdependent intrinsic processes, generation of ever-increasing in-process data and machining domain knowledge. To manage and utilize those above effectively, an industrial dataspace for machining workshop (IDMW) is presented with a three-layer framework. The IDMW architecture isSchema Centralized-Data Distributed, which relies on Process-Workpiece-Centric knowledge schema description and data storage in decentralized data silos. Subsequently, the pre-processing method for the data silos driven by RFID event graphical deduction model is elaborated to associate decentralized data with knowledge schema. Furthermore, through two industrial case studies, it is found that IDMW is effective in managing heterogeneous data, interconnecting the resource entities, handling domain knowledge, and thereby enabling machining operations control on the machining workshop floor particularly.
Authors
I am an author on this paper
Click your name to claim this paper and add it to your profile.
Reviews
Recommended
No Data Available